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1.
Water Res ; 222: 118894, 2022 Jul 23.
Article in English | MEDLINE | ID: covidwho-1956370

ABSTRACT

Antimicrobials like parabens, triclosan (TCS), and triclocarban (TCC) are of public health concern worldwide due to their endocrine-disrupting properties and ability to promote antimicrobial drug resistance in human pathogens. The overall use of antimicrobials presumably has increased during the COVID-19 pandemic, whereas TCS and TCC may have experienced reductions in use due to their recent ban from thousands of over-the-counter (OTC) personal care products by the U.S. Food and Drug Administration (FDA). No quantitative data are available on the use of parabens or the impact the FDA ban had on TCC and TCS. Here, we use wastewater samples (n = 1514) from 10 different communities in Arizona to measure the presence of the six different antimicrobial products (TCS, TCC, and four alkylated parabens [methylparaben (MePb), ethylparaben (EtPb), propylparaben (PrPb), butylparaben (BuPb)]) collected before and during the COVID-19 pandemic using a combination of solid-phase extraction, liquid chromatography/tandem mass spectrometry (LC-MS/MS), and isotope dilution for absolute quantitation. The average mass loadings of all antimicrobials combined (1,431 ± 22 mg/day per 1,000 people) after the onset of the local epidemic (March 2020 - October 2020) were significantly higher (945 ± 62 mg/day per 1,000 people; p < 0.05) than before the pandemic (January 2019 - February 2020). Overall, parabens (∑Pbs = 999 ± 16 mg/day per 1,000 people) were the most used antimicrobials, followed by TCS (117 ± 14 mg/day per 1,000 people) and TCC (117 ± 14 mg/day per 1,000 people). After the 2017 U.S. FDA ban, we found a statistically significant (p < 0.05) reduction in the mass loadings of TCS (-89%) and TCC (-80%) but a rise in paraben use (+72%). Mass flows of 3 of a total of 4 parabens (MePb, EtPb, and PrPb) in wastewater were significantly higher upon the onset of the epidemic locally (p < 0.05). This is the first longitudinal study investigating the use of antimicrobials during the COVID-19 pandemic by employing wastewater-based epidemiology. Whereas an overall increase in the use of antimicrobials was evident from analyzing Arizona wastewater, a notable reduction in the use of TCS and TCC was evident during the pandemic, triggered by the U.S. FDA ban.

2.
Multimed Tools Appl ; 81(19): 27631-27655, 2022.
Article in English | MEDLINE | ID: covidwho-1942433

ABSTRACT

COVID-19 is a viral disease that in the form of a pandemic has spread in the entire world, causing a severe impact on people's well being. In fighting against this deadly disease, a pivotal step can prove to be an effective screening and diagnosing step to treat infected patients. This can be made possible through the use of chest X-ray images. Early detection using the chest X-ray images can prove to be a key solution in fighting COVID-19. Many computer-aided diagnostic (CAD) techniques have sprung up to aid radiologists and provide them a secondary suggestion for the same. In this study, we have proposed the notion of Pearson Correlation Coefficient (PCC) along with variance thresholding to optimally reduce the feature space of extracted features from the conventional deep learning architectures, ResNet152 and GoogLeNet. Further, these features are classified using machine learning (ML) predictive classifiers for multi-class classification among COVID-19, Pneumonia and Normal. The proposed model is validated and tested on publicly available COVID-19 and Pneumonia and Normal dataset containing an extensive set of 768 images of COVID-19 with 5216 training images of Pneumonia and Normal patients. Experimental results reveal that the proposed model outperforms other previous related works. While the achieved results are encouraging, further analysis on the COVID-19 images can prove to be more reliable for effective classification.

3.
Water ; 14(12):1842, 2022.
Article in English | MDPI | ID: covidwho-1884452

ABSTRACT

The COVID-19 pandemic has challenged healthcare systems worldwide. Efforts in low-to-middle-income countries (LMICs) cannot keep stride with infection rates, especially during peaks. A strong international collaboration between Arizona State University (ASU), Tec de Monterrey (TEC), and Servicios de Agua y Drenaje de Monterrey (Local Water Utilities) is acting to integrate wastewater-based epidemiology (WBE) of SARS-CoV-2 in the region as a complementary approach to aid the healthcare system. Wastewater was collected from four sewer catchments in the Monterrey Metropolitan area in Mexico (pop. 4,643,232) from mid-April 2020 to February 2021 (44 weeks, n = 644). Raw wastewater was filtered and filter-concentrated, the RNA was extracted using columns, and the Charité/Berlin protocol was used for the RT-qPCR. The viral loads obtained between the first (June 2020) and second waves (February 2021) of the pandemic were similar;in contrast, the clinical cases were fewer during the first wave, indicating poor coverage. During the second wave of the pandemic, the SARS-CoV-2 quantification in wastewater increased 14 days earlier than the COVID-19 clinical cases reported. This is the first long-term WBE study in Mexico and demonstrates its value in pandemic management.

4.
Hepatology ; 2022 May 14.
Article in English | MEDLINE | ID: covidwho-1843915

ABSTRACT

BACKGROUND AND AIMS: A few case reports of autoimmune hepatitis-like liver injury have been reported after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination. We evaluated clinical features, treatment response and outcomes of liver injury following SARS-CoV-2 vaccination in a large case series. APPROACH AND RESULTS: We collected data from cases in 18 countries. The type of liver injury was assessed with the R-value. The study population was categorized according to features of immune-mediated hepatitis (positive autoantibodies and elevated immunoglobulin G levels) and corticosteroid therapy for the liver injury. We identified 87 patients (63%, female), median age 48 (range: 18-79) years at presentation. Liver injury was diagnosed a median 15 (range: 3-65) days after vaccination. Fifty-one cases (59%) were attributed to the Pfizer-BioNTech (BNT162b2) vaccine, 20 (23%) cases to the Oxford-AstraZeneca (ChAdOX1 nCoV-19) vaccine and 16 (18%) cases to the Moderna (mRNA-1273) vaccine. The liver injury was predominantly hepatocellular (84%) and 57% of patients showed features of immune-mediated hepatitis. Corticosteroids were given to 46 (53%) patients, more often for grade 3-4 liver injury than for grade 1-2 liver injury (88.9% vs. 43.5%, p = 0.001) and more often for patients with than without immune-mediated hepatitis (71.1% vs. 38.2%, p = 0.003). All patients showed resolution of liver injury except for one man (1.1%) who developed liver failure and underwent liver transplantation. Steroid therapy was withdrawn during the observation period in 12 (26%) patients after complete biochemical resolution. None had a relapse during follow-up. CONCLUSIONS: SARS-CoV-2 vaccination can be associated with liver injury. Corticosteroid therapy may be beneficial in those with immune-mediated features or severe hepatitis. Outcome was generally favorable, but vaccine-associated liver injury led to fulminant liver failure in one patient.

5.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-335469

ABSTRACT

This paper presents the evaluation of air quality in different districts of Haryana. Geo-spatial techniques were used to estimate gaseous and particulate pollutant's spatial and temporal variation during complete nationwide lockdown period and same month of previous year 2019 (March to May). Data of six fixed pollutants were collected from Central Pollution Control Board (CPCB). In this context, the data of air pollutants (PM 10, PM 2.5, O 3 , NOx, SO 2 , and CO) were analyzed for 2019 and 2020. The Spatio-temporal distribution of the Air Quality Index (AQI) clearly depicts difference in lockdown and unlock period. The result was showed that the air quality was very poor to satisfactory in 2019 and a improvement was observed from satisfactory to good in 2020 due to COVID-19 lockdown. The study suggests that air quality will be improved by the best utilization of straw burning, automobiles and reduce major pollutant sources.

6.
Decis Support Syst ; : 113792, 2022 May 06.
Article in English | MEDLINE | ID: covidwho-1821207

ABSTRACT

The COVID-19 pandemic has had a severe impact on mankind, causing physical suffering and deaths across the globe. Even those who have not contracted the virus have experienced its far-reaching impacts, particularly on their mental health. The increased incidences of psychological problems, anxiety associated with the infection, social restrictions, economic downturn, etc., are likely to aggravate with the virus spread and leave a longer impact on humankind. These reasons in aggregation have raised concerns on mental health and created a need to identify novel precursors of depression and suicidal tendencies during COVID-19. Identifying factors affecting mental health and causing suicidal ideation is of paramount importance for timely intervention and suicide prevention. This study, thus, bridges this gap by utilizing computational intelligence and Natural Language Processing (NLP) to unveil the factors underlying mental health issues. We observed that the pandemic and subsequent lockdown anxiety emerged as significant factors leading to poor mental health outcomes after the onset of COVID-19. Consistent with previous works, we found that psychological disorders have remained pre-eminent. Interestingly, financial burden was found to cause suicidal ideation before the pandemic, while it led to higher odds of depressive (non-suicidal) thoughts for individuals who lost their jobs. This study offers significant implications for health policy makers, governments, psychiatric practitioners, and psychologists.

7.
Clinical Epidemiology and Global Health ; : 101044, 2022.
Article in English | ScienceDirect | ID: covidwho-1783224

ABSTRACT

Introduction Newer coexisting conditions should be identified in order to modify newer risk factors. Aim was to identify patients with non-classical or less common coexisting conditions in patients infected of COVID 19. Method Single centred study from June 2020 to May 2021 at a tertiary centre in North India. A preformed questionnaire was used to record clinical and laboratory parameters and to identify cases which are in addition to CDC list and Indian data. Results 0.67% (46) cases out of 6832 patients were identified to have non-classical coexisting illness. It was divided into 2 groups-infections A (60.1%) and non-infections B (39.9%). Group A included-tuberculosis- pulmonary (14.3%) & extra pulmonary (32.9%), bacterial (25.0%) viral infections [dengue, hepatitis B & C] (14.3%), HIV disease (10.7%) and malaria (3.6%). Group B included- organ transplant (27.8%), autoimmune [myasthenia gravis, polymyositis, psoriasis] (22.6%), haematologic [Haemophilia, ITP, Aplastic anaemia, APML, CML] (27.8%), uncommon malignancies [disseminated sacral chordoma and GTN] (11.1%) and snakebite (11.1%). Serum Procalcitonin was not helpful for diagnosis of bacterial infection in COVID-19 disease. Group A had significantly longer duration of illness, hepatitis and elevated CRP. The mortality in group A & B were 32.1% and 43.8% respectively. Death in non-severe COVID cases was in tetanus and snakebite. 30.7% death among tuberculosis patients. More than 70% of deaths were attributable to COVID 19 in both the groups. Conclusion In Indian settings, comorbidities like tuberculosis and bacterial infections can precipitate severe COVID 19 unlike other parts of the world where tuberculosis is relatively uncommon.

8.
SSRN;
Preprint in English | SSRN | ID: ppcovidwho-326412

ABSTRACT

The COVID-19 pandemic caused by the SARS-CoV-2 virus has challenged healthcare systems worldwide. Efforts to monitor the prevalence of SARS-CoV-2 through large-scale clinical testing have proved relatively successful in countries with low population densities, effective health care systems, and strong economies. However, efforts at the aforementioned scale are not possible for low-middle income countries (LMIC), especially those with dense populations where testing cannot keep stride with infection rates, and costs serve as a barrier to participation. Here we developed a strong international collaboration, Arizona State University (ASU), Tec de Monterrey (TEC), and Servicios de Agua y Drenaje de Monterrey, to aid LMIC populations by integrating wastewater-based epidemiology (WBE) into healthcare surveillance by monitoring SARS-CoV-2 in wastewater as a complementary approach and additional data stream for decision makers. In this study, wastewater was collected in 4 sewer catchments throughout the Monterrey Metropolitan area in Mexico (pop. 4,643,232) from mid-April 2020 to February 2021 (44 weeks, n =644), immediately shipped to ASU), and analyzed for SARS-CoV-2 by RT-qPCR targeting the E gene. Results were electronically transmitted to TEC and disseminated to Servicios de Agua y Drenaje de Monterrey (Nuevo Leon State Water Utility). Here, although viral load between the first (May to August 2020) and second waves (November 2020 to February 2021) of the pandemic were similar, clinical cases during the first wave were fewer, indicating poorer clinical testing coverage. In the second wave of the pandemic, wastewater preceded COVID-19 clinical cases by 14 days, acting as an early warning system for communities. This is the first long-term use of WBE to monitor SARS-CoV-2 wastewater in Mexico and demonstrates the utility of the WBE methodology in SARS-CoV-2 pandemic management in LMIC, where access to individualized PCR tests is not available for all populations.

9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314676

ABSTRACT

SARS-CoV2, a new coronavirus has emerged in Wuhan city of China, December last year causing pneumonia named COVID-19 which has now spread to entire world. By April 2020, number of confirmed cumulative cases crossed ~2.4 million worldwide, according to WHO. Till date, no effective treatment or drug is available for this virus. Availability of X-ray structures of SARS-CoV2 main protease (Mpro) provided the potential opportunity for structure based drug designing. Here, we have made an attempt to do computational drug design by targeting main protease of SARS-CoV2. Highthroughput virtual screening of million molecules and natural compounds databases was performed followed by docking. Six ligands showed better binding affinities which were further optimized by MD simulation and rescoring of binding energy was calculated through MM/PBSA method. In addition, conformational effect of various ligands on protein was examined through essential dynamics simulation. Three compounds namely ZINC14732869, ZINC19774413 and ZINC19774479 were finally filtered that displayed high binding free energies than N3 inhibitor and form conformationally stable complex. Hence, current study features the discovery of novel inhibitors for main protease of CoV2 which will provide effective therapeutic candidates against COVID19.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309161

ABSTRACT

COVID-19 is an infectious disease, growth of which depends upon the linked stages of the epidemic, the average number of people one person can infect and the time it takes for those people to become infectious themselves. We have studied the COVID-19 time series to understand the growth behaviour of COVID-19 cases series. A structural break occurs in the COVID-19 series at the change time form one stage to another. We have performed the structural break analysis of data available for 207 countries till April 20, 2020. There are 42 countries which have recorded five breaks in COVID cases series. This means that these countries are in the sixth stage of growth transmission and show a downward pattern in reporting in the daily cases, whereas countries with two and three breaks, record the rapid growth pattern in the daily cases. From this study, we conclude that the more the breaks in the series, there is more possibility to determine the constant or decreasing rate of daily cases. It is well fitted using lognormal distribution as this distribution is archived at its highest peak after some period and then suddenly it decreases at a longer time period. This can be seen in various countries like China, Australia, New Zealand and so on.

11.
Biosensors (Basel) ; 12(2)2022 Jan 29.
Article in English | MEDLINE | ID: covidwho-1677659

ABSTRACT

Viral infections are becoming the foremost driver of morbidity, mortality and economic loss all around the world. Treatment for diseases associated to some deadly viruses are challenging tasks, due to lack of infrastructure, finance and availability of rapid, accurate and easy-to-use detection methods or devices. The emergence of biosensors has proven to be a success in the field of diagnosis to overcome the challenges associated with traditional methods. Furthermore, the incorporation of aptamers as bio-recognition elements in the design of biosensors has paved a way towards rapid, cost-effective, and specific detection devices which are insensitive to changes in the environment. In the last decade, aptamers have emerged to be suitable and efficient biorecognition elements for the detection of different kinds of analytes, such as metal ions, small and macro molecules, and even cells. The signal generation in the detection process depends on different parameters; one such parameter is whether the labelled molecule is incorporated or not for monitoring the sensing process. Based on the labelling, biosensors are classified as label or label-free; both have their significant advantages and disadvantages. Here, we have primarily reviewed the advantages for using aptamers in the transduction system of sensing devices. Furthermore, the labelled and label-free opto-electrochemical aptasensors for the detection of various kinds of viruses have been discussed. Moreover, numerous globally developed aptasensors for the sensing of different types of viruses have been illustrated and explained in tabulated form.


Subject(s)
Aptamers, Nucleotide , Biosensing Techniques , Virus Diseases , Viruses , Aptamers, Nucleotide/chemistry , Biosensing Techniques/methods , Humans , Viruses/isolation & purification
12.
Asian Journal of Economics and Banking (AJEB) ; 5(1):2-14, 2021.
Article in English | ProQuest Central | ID: covidwho-1595082

ABSTRACT

PurposeThe present world is crippled with the pandemic coronavirus (Covid-19). The pandemic that originated in Wuhan city of China has sent every country in the world in an unprecedented situation that has social and economic impacts. This paper aims to explore whether epidemics and pandemics have any impact on consumption patterns among rural and urban consumers in India. Taking pandemic Covid-19 as a case study, it was explored how this pandemic impacted the consumption pattern of consumers in India;what are the similarities and/or differences between rural and urban consumers that are found in their consumption habits in the wake of Covid-19 pandemic.Design/methodology/approachThe required data was collected through questionnaires sent to respondents. Approximately 500 respondents were contacted through the mail to fill in the survey questionnaire. Despite the sincere efforts, a total of 175 complete survey questionnaires were filled in by respondents. The study used SPSS Statistics version 25 software for the analysis of data.FindingsIt was found that epidemics and pandemics have a profound impact on the pattern of consumption in India. The study reveals that consumers resort to panic buying in the initial stages of epidemics and pandemics. It was found that consumption habits of consumers went a sea change and they were spending largely on essentials only. The study also reveals that the majority of consumers would like to continue in the same consumption habits as that of during COVID-19. The consumption pattern of urban consumers witnessed more change than the consumption pattern of rural consumers. It is due to the closure of eateries and restaurants, shopping malls, movie theatres, etc., in urban areas that forced the change in the consumption pattern of urban consumers.Research limitations/implicationsThe research has a limitation of using a less sample size. For the generalizations, more robust studies can be conducted with more data.Practical implicationsThe findings of the study will give marketers an insight for framing their policies in the wake of epidemics and pandemics.Originality/valueThe research adds to the existing body of knowledge. There are plenty of studies on the behaviour of consumers. However, there are no major studies that focus on the behaviour of consumers during the outbreak of a pandemic. So, this study fills this gap in the existing body of knowledge.

13.
Comput Methods Programs Biomed ; 215: 106594, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1588051

ABSTRACT

BACKGROUND AND OBJECTIVES: Remarkable infectivity of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) is due to the rapid emergence of various strains which enable the virus to ruling the world. Over the course of SARS-CoV2 pandemic, the scientific communities worldwide are responding to newly emerging genetic variants. However, mechanism behind the persistent infection of these variants is still not known due to the paucity of study of these variants at molecular level. In this scenario, computational methods have immense utility in understanding the molecular and functional properties of different variants. METHODS: The various mutants (MTs) of SpikeS1 receptor binding domain (RBD) of highly infectious SARS-CoV2 strains were manifested and elucidated the protein structure and binding strength using molecular dynamics (MD) simulation and protein-protein docking approaches. RESULTS: MD simulation study showed that all MTs exhibited stable structures with altered functional properties. Furthermore, the binding strength of different MTs along with WT (wildtype) was revealed that MTs showed differential binding affinities to host protein with high binding strength exhibited by V367F and V483A MTs. CONCLUSION: Hence, this study shed light on the molecular basis of infection caused by different variants of SARS-CoV2, which might play an important role in to cease the transmission and pathogenesis of virus and also implicate in rational designing of a specific drug.


Subject(s)
COVID-19 , Spike Glycoprotein, Coronavirus , Humans , Protein Binding , RNA, Viral , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/metabolism
14.
Water Res ; 205: 117710, 2021 Oct 15.
Article in English | MEDLINE | ID: covidwho-1450241

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.


Subject(s)
COVID-19 , SARS-CoV-2 , High-Throughput Nucleotide Sequencing , Humans , Pandemics , Waste Water
15.
Phys Eng Sci Med ; 44(4): 1257-1271, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1450021

ABSTRACT

According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impact. The main challenge in fighting against this disease is its scale. Due to the outbreak, medical facilities are under pressure due to case numbers. A quick diagnosis system is required to address these challenges. To this end, a stochastic deep learning model is proposed. The main idea is to constrain the deep-representations over a Gaussian prior to reinforce the discriminability in feature space. The model can work on chest X-ray or CT-scan images. It provides a fast diagnosis of COVID-19 and can scale seamlessly. The work presents a comprehensive evaluation of previously proposed approaches for X-ray based disease diagnosis. The approach works by learning a latent space over X-ray image distribution from the ensemble of state-of-the-art convolutional-nets, and then linearly regressing the predictions from an ensemble of classifiers which take the latent vector as input. We experimented with publicly available datasets having three classes: COVID-19, normal and pneumonia yielding an overall accuracy and AUC of 0.91 and 0.97, respectively. Moreover, for robust evaluation, experiments were performed on a large chest X-ray dataset to classify among Atelectasis, Effusion, Infiltration, Nodule, and Pneumonia classes. The results demonstrate that the proposed model has better understanding of the X-ray images which make the network more generic to be later used with other domains of medical image analysis.


Subject(s)
COVID-19 , Deep Learning , Algorithms , Humans , Neural Networks, Computer , SARS-CoV-2 , X-Rays
16.
Clin Nutr ESPEN ; 46: 21-32, 2021 12.
Article in English | MEDLINE | ID: covidwho-1439951

ABSTRACT

The catastrophic pandemic engendered due to the Novel coronavirus (COVID-19) outbreak which causes severe clinical afflictions on the respiratory system has severely high morbidity and mortality rates. The requirement of novel compounds is at utmost importance due to lack of targeted drug molecule to treat the afflictions and restrict the viral infection and for the usage of prophylactic treatment to avoid the spread of the infection is of utmost importance. Vitamin D is one such naturally available multifunctional molecule, which plays an eminent role in the immune system and instigation of numerous cellular pathways further promoting health benefits and enhancing the human quality of life. This article reviews the current standpoint scenario and future prevalence of vitamin D supplementation in the management of covid-19 patients. Novel findings of Vitamin D suggest that along with regulation of cell growth, neuroprotective and mood-stabilizing effects, it regulates the immune response also modulate cytokine Interleukin-6 (IL-6) by inducing progesterone-induced blocking factor (PIBF), given the IL-6 levels are considerably high in COVID-19 patients which increases the further complications. Vitamin D also have its effect on angiotensin converting enzyme (ACEII) inhibitor through which the COVID-19 virus makes cell entry. Numerous research data elucidate the play of Vitamin D, in complications of COVID-19 including the most common comorbid conditions, neurological manifestations and immunological aspects makes it an ideal molecule for adjuvant therapy. Including Vitamin D as add-on therapy in the management of COVID-19 might aid the arrest of infection and helps fight this arduous epidemic.


Subject(s)
COVID-19 , Vitamins , Humans , Quality of Life , SARS-CoV-2 , Sunlight
17.
PLoS ONE ; 16(2), 2021.
Article in English | CAB Abstracts | ID: covidwho-1410575

ABSTRACT

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.

18.
Brain Disord ; 4: 100021, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1385424

ABSTRACT

Coronaviruses have emerged as alarming pathogens owing to their inherent ability of genetic variation and cross-species transmission. Coronavirus infection burdens the endoplasmic reticulum (ER.), causes reactive oxygen species production and induces host stress responses, including unfolded protein response (UPR) and antioxidant system. In this study, we have employed a neurotropic murine ß-coronavirus (M-CoV) infection in the Central Nervous System (CNS) of experimental mice model to study the role of host stress responses mediated by interplay of DJ-1 and XBP1. DJ-1 is an antioxidant molecule with established functions in neurodegeneration. However, its regulation in virus-induced cellular stress response is less explored. Our study showed that M-CoV infection activated the glial cells and induced antioxidant and UPR genes during the acute stage when the viral titer peaks. As the virus particles decreased and acute neuroinflammation diminished at day ten p.i., a significant up-regulation in UPR responsive XBP1, antioxidant DJ-1, and downstream signaling molecules, including Nrf2, was recorded in the brain tissues. Additionally, preliminary in silico analysis of the binding between the DJ-1 promoter and a positively charged groove of XBP1 is also investigated, thus hinting at a mechanism behind the upregulation of DJ-1 during MHV-infection. The current study thus attempts to elucidate a novel interplay between the antioxidant system and UPR in the outcome of coronavirus infection.

20.
Indian J Crit Care Med ; 25(5): 584-587, 2021 May.
Article in English | MEDLINE | ID: covidwho-1229413

ABSTRACT

Spontaneous air-leak syndromes have emerged as rare but significant complication of Coronavirus disease-2019 (COVID-19) pneumonia in the last few months. This complication has been documented in both spontaneous and mechanically ventilated patients. Although few studies have used computed tomographic scans to confirm the diagnosis, this could be challenging in resource-limited setup. We present a series of 15 cases that highlight the clinical heterogeneity with respect to stage of illness, ventilatory status, and varied clinical scenarios at the time of development of these syndromes. All cases in our series were diagnosed clinically and confirmed by bedside chest X-ray and were managed promptly. Though mortality was not so infrequent in our experience, these air-leak syndromes were not directly attributed as cause of death in these patients. Therefore, high level of clinical suspicion and vigilance is necessary to identify and manage cases of air-leak syndrome. How to cite this article: Sabharwal P, Chakraborty S, Tyagi N, Kumar R, Taneja A. Spontaneous Air-leak Syndrome and COVID-19: A Multifaceted Challenge. Indian J Crit Care Med 2021;25(5):584-587.

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